Mechanisms of land-atmosphere in the Sahel Christopher Taylor Centre for Ecology and Hydrology, Wallingford, U.K. Richard Ellis, Phil Harris (CEH) Doug Parker (Leeds)

Outline Soil moisture - rainfall feedbacks on daily timescales Satellite analysis Aircraft observations (AMMA) –A dry case –A wet case

Soil moisture – rainfall feedbacks Koster et al, Science 2004 Shows where climate models sensitive to soil moisture Large “coupling strength” implies soil moisture has significant impact on precipitation i.e. feedback possible Large variations between models - models don’t represent basic processes well. Do we have observations to judge models by? Focus on West African “hotspot”

How strong should coupling be? What are mechanisms? Are our parameterisations suitable?

Daily Variability in Surface Fluxes in Sahel Evaporation limited by soil moisture so fluxes very sensitive to rainfall For several days after rain: –large evaporation rates direct from soil –low sensible heat flux –low surface temperature Observations from savanna site at the start of the 1990 wet season (Gash et al)

Does daily surface variability matter in a GCM? Variations in surface fluxes on short timescales feed-back on simulated rainfall. Taylor and Clark, QJRMS (2001) Power spectra of simulated rainfall in HadAM3

Impact of soil moisture on afternoon convection Wet soil 12 June :15 Meteosat 7 TIR In this single case, extent of convective system influenced by soil moisture… Convection “avoids” wet soil 13 June Polarisation ratio TMI

Results from 108 cases Over 50% cases similar to example shown 33% less cloud over wet soil than nearby drier zones Initiation over wet soil strongly suppressed (2% cases) Suggests a negative soil moisture – precipitation feedback for initiating storms (cf Taylor and Lebel 1998) Potential mechanisms? Cold cloud extent 13 June Taylor and Ellis, GRL 2006

Aircraft Observations: African Monsoon Multidisciplinary Analyses Special Observing Period during 2006 Wet Season Focussed observations at multiple ground sites and with 5 aircraft, including NERC/Met Office BAe146 5 week deployment in Niamey, Niger

A dry case study: 1 August Z Aug 1 17:00 UTC 31 July NiameyInitiating storm Meteosat thermal infra-red 00:00 UTC 1 Aug 12:00 UTC 1 Aug

Global View

Flight over storm track 18 hours later Polarisation ratio anomalies from TRMM Spatial resolution ~ 50 km Storm track Flight track 1000 km

Cold (wet)Warm (dry) Storm track Red contours show overnight storm from cloud top temperature Land Surface Temperature Anomalies Extract mean diurnal cycle to obtain Land Surface Temperature Anomaly (LSTA) 500 km White: no data (cloud or river)

Aircraft data within planetary boundary layer (PBL) Wettest soils Observed PBL temperature Generally very good correlation between satellite surface data and PBL at fine scale: weak heating from wet soil>cool PBL PBL temperature according to ECMWF forecast model Land surface temperature anomaly (satellite) PBL gradient due to vegetation feature

Aircraft data within planetary boundary layer (PBL) Similar story for specific humidity High values above wet surface

Vertical profile data (dropsondes) Pressure PBL twice as deep over dry soil as wet, and markedly drier and cooler. More inhibition to convection over wet soil. In fact, no significant convection on this afternoon along track. X X X: lifting condensation level Wet soil Dry soil

An impact on low level winds? If surface heating contrasts large enough, might expect a sea-breeze type response… i.e. convergence over dry (hot) surfaces So surface gradients ARE strong enough to induce circulations.

Low level wind vectors Convergence Divergence Convergence Analysis suggests that soil moisture patterns strong enough to induce sea-breeze type circulations. Can they cause further storms on more favourable days? Land surface temperature anomaly

A wet case study: 31 July 2006 Had similar flight planned previous afternoon… Very dry surface bounded by wet areas wet dry

Storm initiation during flight System developed very rapidly over dry soil as we approached. Aircraft track

Storm initiation Due to convective inhibition or convergent winds? Clouds over dry soil

Early evolution of storm Shading: land surface temperature (red=dry) Contours: cloud from visible channel Storm develops along wet-dry surface contrast Signature of triggering by circulation rather than thermodynamic profiles

Current work in AMMA Quantifying surface fluxes (ALMIP) –Best available met forcing –Surface flux obs to calibrate models –Assimilation of LST data Feedbacks on convective initiation –Role of circulations and/or thermodynamic profiles MCS feedbacks –Sign and strength of feedback –Key space scales Intraseasonal feedbacks –Wet/dry spells Interannual memory –vegetation Observational diagnostics to test atmospheric models

Hombori Tondo (Mali) from UK BAe146. Photo: Doug Parker

Soil moisture and monsoon dynamics Intraseasonal variability in West African rainfall –Large-scale wetting/drying 15 day cycle Cause and effect? Satellite soil moisture Surface heating (W/m2) Atmospheric warming T 925hPa (ECMWF)

Cause and effect: lagged relationships Composite data based on surface wetting TMI wetness Satellite cold cloud ERA40 Temperature anomalies Additional daytime cooling at 925hPa day 0 and day 1 - shows soil moisture leads to cooling in ECMWF analyses

Wet v Dry Spells During wet spells, “cool high” develops across Sahel Dynamic response to soil moisture consistent with forcing of variability Studentship with UEA looking at feedbacks in GCM Shading: surface heating Contours: 925hPa Temperature

Convective scale feedbacks From observations, found tendency of rain within squall lines to be heavier in locations that have been recently wetted Linked to a positive feedback between soil moisture and rainfall at scales of only km (Taylor and Lebel, MWR 1998) 20 July July 1992 Rain gauge data from HAPEX-Sahel

Modelling Impact of Moisture Anomalies on Convection Used cloud-resolving model (RAMS) to assess impact of humidity on cloud-scale dynamics within squall line. Run large ensembles. Introduce wet patch of additional 1g/kg in lowest 1km Strong impact of patch on simulated rainfall 10 km 14 km 21 km Impact sensitive to patch length scale Unexpected sensitivity of feedbacks to length scale, convection sensitive to fine scale variability (Clark et al 2003 QJRMS, 2004 JHMet)

Synoptic Scale Surface Variability Screened TIR anomalies are well-organised at large scale (~ km) in N. Sahel Warm Cool

Synoptic Scale Surface Variability Alternate warm (dry) and cool (wet) surface anomalies travel westwards across the Sahel Longitude Day Black lines: cold cloud Cool surface features appear after rain

TIR [C] Impact of Synoptic Surface Variability on Atmosphere? Degrees longitude Anomaly Produced composite “hotspot” from 2000 wet season to assess feedback of surface on atmosphere km higher atmospheric temperatures lower surface pressure vortex develops Southerlies Northerlies subsequent cold cloud (rainfall) modulated Observational analyses suggest: Taylor et al QJRMS 2005

Identifying Wet Soil From Satellite Several possibilities for detecting soil moisture from space Passive microwave (10.65 GHz) from TRMM Microwave Imager to infer wet soil (high evaporation) after recent rain Rainfall (bars) and TRMM polarisation ratio (asterisks) in Banizoumbou region (Niger) Soil drying after rain Rainfall data courtesy of T. Lebel (IRD)

Thermal Data Meteosat Second Generation provides data every 15 mins at high spatial resolution (~3 km) Land surface temperature products produced by LandSAF in near real time